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Framework for determining airport daily departure and arrival delay thresholds: statistical modelling approach
The study derives a framework for assessing airport efficiency through evaluating optimal arrival and departure delay thresholds. Assumptions of airport efficiency measurements, though based upon minimum numeric values such as 15 min of turnaround time, cannot be extrapolated to determine proportion...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4938809/ https://www.ncbi.nlm.nih.gov/pubmed/27441145 http://dx.doi.org/10.1186/s40064-016-2623-5 |
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author | Wesonga, Ronald Nabugoomu, Fabian |
author_facet | Wesonga, Ronald Nabugoomu, Fabian |
author_sort | Wesonga, Ronald |
collection | PubMed |
description | The study derives a framework for assessing airport efficiency through evaluating optimal arrival and departure delay thresholds. Assumptions of airport efficiency measurements, though based upon minimum numeric values such as 15 min of turnaround time, cannot be extrapolated to determine proportions of delay-days of an airport. This study explored the concept of delay threshold to determine the proportion of delay-days as an expansion of the theory of delay and our previous work. Data-driven approach using statistical modelling was employed to a limited set of determinants of daily delay at an airport. For the purpose of testing the efficacy of the threshold levels, operational data for Entebbe International Airport were used as a case study. Findings show differences in the proportions of delay at departure (μ = 0.499; 95 % CI = 0.023) and arrival (μ = 0.363; 95 % CI = 0.022). Multivariate logistic model confirmed an optimal daily departure and arrival delay threshold of 60 % for the airport given the four probable thresholds {50, 60, 70, 80}. The decision for the threshold value was based on the number of significant determinants, the goodness of fit statistics based on the Wald test and the area under the receiver operating curves. These findings propose a modelling framework to generate relevant information for the Air Traffic Management relevant in planning and measurement of airport operational efficiency. |
format | Online Article Text |
id | pubmed-4938809 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-49388092016-07-20 Framework for determining airport daily departure and arrival delay thresholds: statistical modelling approach Wesonga, Ronald Nabugoomu, Fabian Springerplus Research The study derives a framework for assessing airport efficiency through evaluating optimal arrival and departure delay thresholds. Assumptions of airport efficiency measurements, though based upon minimum numeric values such as 15 min of turnaround time, cannot be extrapolated to determine proportions of delay-days of an airport. This study explored the concept of delay threshold to determine the proportion of delay-days as an expansion of the theory of delay and our previous work. Data-driven approach using statistical modelling was employed to a limited set of determinants of daily delay at an airport. For the purpose of testing the efficacy of the threshold levels, operational data for Entebbe International Airport were used as a case study. Findings show differences in the proportions of delay at departure (μ = 0.499; 95 % CI = 0.023) and arrival (μ = 0.363; 95 % CI = 0.022). Multivariate logistic model confirmed an optimal daily departure and arrival delay threshold of 60 % for the airport given the four probable thresholds {50, 60, 70, 80}. The decision for the threshold value was based on the number of significant determinants, the goodness of fit statistics based on the Wald test and the area under the receiver operating curves. These findings propose a modelling framework to generate relevant information for the Air Traffic Management relevant in planning and measurement of airport operational efficiency. Springer International Publishing 2016-07-08 /pmc/articles/PMC4938809/ /pubmed/27441145 http://dx.doi.org/10.1186/s40064-016-2623-5 Text en © The Author(s) 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Research Wesonga, Ronald Nabugoomu, Fabian Framework for determining airport daily departure and arrival delay thresholds: statistical modelling approach |
title | Framework for determining airport daily departure and arrival delay thresholds: statistical modelling approach |
title_full | Framework for determining airport daily departure and arrival delay thresholds: statistical modelling approach |
title_fullStr | Framework for determining airport daily departure and arrival delay thresholds: statistical modelling approach |
title_full_unstemmed | Framework for determining airport daily departure and arrival delay thresholds: statistical modelling approach |
title_short | Framework for determining airport daily departure and arrival delay thresholds: statistical modelling approach |
title_sort | framework for determining airport daily departure and arrival delay thresholds: statistical modelling approach |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4938809/ https://www.ncbi.nlm.nih.gov/pubmed/27441145 http://dx.doi.org/10.1186/s40064-016-2623-5 |
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